USGS-NAWQA: WARP
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Title
| Watershed Regressions for Pesticides (WARP) |
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Author
| US Geological Survey |
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Abstract/Summary Statement
| The WARP model predicts specific concentration statistics for a selected pesticide. Assessment and management of pesticides require far more information than we can afford to directly measure for all the places, times, and pesticides of interest. In addition, many decisions-such as setting monitoring priorities, approving registration of a new pesticide, and determining how much to spend on a management strategy-inherently depend on predicting the potential effects of pesticides on water quality for locations or amounts of use that have never been directly assessed. In these situations, statistical models and other types of models are used for predicting water-quality conditions at unmonitored locations under a range of possible circumstances. The National Water Quality Assessment (NAWQA) Program is developing a series of statistical models, based on monitoring data and watershed characteristics, to enable estimation of pesticide concentrations for streams that have not been monitored. The Watershed Regression for Pesticides models are referred to as WARP models. |
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Table of Contents
| Website and companion report |
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Citation
| Stone, W.W.,and Gilliom, R.J., 2009, Update of watershed regressions for pesticides (WARP) for predicting atrazine concentration in streams: U.S. Geological Survey Open-File Report 2009¿1122, 22 p. |
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Method Source
| USGS-NAWQA |
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Source Organization Country
| USA |
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Publication Year
| 2009 |
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Special Notes
| A complete description of the development and performance of the atrazine WARP model is provided by Stone and Gilliom (2009), at http://pubs.usgs.gov/of/2009/1122/ |
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Item Type
| Website |
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Publication Source Type
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Government Agency (Federal, USA) |
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Purpose
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Data analysis |
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Design or Data Analysis Objectives
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Flow-adjusted concentrations Interpolate concentrations Revisit Spatial trends |
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Complexity
| Medium |
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Media Emphasized
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Surface Water |
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Media Subcategory
| |
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Special Topics
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